Principal Associate, Data Science - US Card

Capital One Capital One · Banking · McLean, VA +3

This role focuses on developing and implementing machine learning models for credit outcomes forecasting within the US Card Intelligence Segments organization. It involves applying explainability techniques, creating AI-model-based decisioning frameworks in a regulated industry, and collaborating with cross-functional teams. The ideal candidate has strong data analysis, statistical modeling, and machine learning experience, with a preference for applied research and explainability.

What you'd actually do

  1. Develop modeling approaches to forecast credit outcomes in a rapidly changing economic environment
  2. Apply cutting-edge explainability techniques to identify insights from complex models
  3. Develop frameworks for AI-model-based decisioning in a highly regulated industry
  4. Collaborate on a cross-functional team with a wide range of specializations and experience

Skills

Required

  • Bachelor's Degree in a quantitative field or equivalent experience
  • 5 years of experience performing data analytics
  • Experience with Python, Scala, or R
  • Experience with machine learning

Nice to have

  • Master's Degree in an applied research field
  • 3 years of experience in data science
  • Experience in explainability
  • Experience with distributed computing

What the JD emphasized

  • highly regulated industry

Other signals

  • develop modeling approaches to forecast credit outcomes
  • apply cutting-edge explainability techniques
  • develop frameworks for AI-model-based decisioning